1. Field of the Invention
The present invention relates to machine vision, and more particularly, to a method for detecting circles in images taken under various lighting conditions.
2. Discussion of Related Art
Detecting a circle in an image is a basic task needed for computer vision, for example, in Surface Mounted Device (SMD) inspection applications. Typically, a Hough transform is used for computerized circle and curve detection. The principle of the Hough transform is to detect parameterized curves by mapping image edge pixels into manifolds in a parameter space and finding peaks using a multidimensional histogram procedure. This method, however, is expensive in terms of computation and memory needs. Typically, due to memory storage limitations, this method also has discretization error in both the image and the parameter space.
Several methods have been proposed to improve Hough transform techniques in terms of efficiency, accuracy and memory storage. One modified scheme uses gradient orientation from edge points. A probabilistic Hough transform attempts to reduce redundant information by sampling image data in various ways. A randomized Hough transform is proposed to detect a curve with n parameters by randomly picking n pixels and mapping them into one point in the parameter space, instead of transforming one pixel into a hyperplane in n-dimensional parameter space. Other methods, such as a generalization Hough transform and a decomposed Hough transform, have been proposed to improve Hough transform techniques. However, the above-mentioned methods are Hough transformation based and are therefore, generally slow.
No known system or method exists for detecting circles in various illumination conditions. Therefore, a need exists for an adaptive method for determining suitable threshold values for various illuminations.